Background Effective treatment is needed for advanced, inoperable, or chemotherapy-resistant cervical cancer patients. Immunotherapy has become a new treatment modality for cervical cancer patients, and there is an urgent need to identify additional targets for cervical cancer immunotherapy. Methods In this study the core gene, RGS1, which affects immune status and the FIGO stage of cervical cancer patients was identified by WGCNA analysis and differential analysis using TCGA database. 10 related genes interacting with RGS1 were identified using PPI network, and the functional and immune correlations were analyzed. Based on the expression of RGS1 and related genes, the consensus clustering method was used to divide CESC patients into two groups (group 1, high expression of RGS1; group 2, low expression of RGS1). Then, the functional enrichment analysis was used to search for the functional differences in differentially expressed genes (DEGs) between group 1 and group 2. Immune infiltration analysis was performed using ESTIMATE, CIBERSORT, and ssGSEA, and the differences in expression of immune checkpoint inhibitors (ICIs) targets were assessed between the two groups. We investigated the effect of RGS1 on the clinical relevance of CESC patients, and experimentally verified the differences in RGS1 expression between cervical cancer patient tissues and normal cervical tissues, the role of RGS1 in cell function, and the effect on tumor growth in tumor-bearing mice. Results We found that RGS1 was associated with CD4, GNAI3, RGS2, GNAO1, GNAI2, RGS20, GNAZ, GNAI1, HLA-DRA and HLA-DRB1, especially CD4 and RGS2. Functional enrichment of DEGs was associated with T cell activation. Compared with group 2, group 1 had stronger immune infiltration and higher ICI target expression. RGS1 had higher expression in cervical cancer tissues than normal tissues, especially in HPV-E6 positive cancer tissues. In cervical cancer cell lines, knockdown of RGS1 can inhibited cell proliferation, migration, invasion, and tumor growth in nude mice and promoted apoptosis. Conclusions RGS1, as an oncogenic gene of cervical cancer, affects the immune microenvironment of patients with cervical cancer and may be a target of immunotherapy.
MicroRNAs (miRNAs) are a type of small noncoding RNAs that often play important roles in carcinogenesis, but the carcinogenic mechanism of miRNAs is still unclear. This study will investigate the functions and the mechanism of miR-638 in osteosarcoma (OS). The expression of miR-638 in OS and the DNA copy number of miR-638 were detected by real-time PCR. The effect of miR-638 on cell proliferation was measured by CCK8 assay. Different assays, including bioinformatics algorithms, luciferase report assay, and Western blotting, were used to identify the target gene proviral integration site for Moloney murine leukemia virus 1 (PIM1) of miR-638 in OS. The expression of PIM1 in clinical OS tissues was also validated by immunohistochemical assay. From this research, we found that miR-638 was downregulated in OS tissues compared with corresponding noncancerous tissues (NCTs), and the DNA copy number of miR-638 was lower in OS than in NCTs, which may induce the corresponding downregulation of miR-638 in OS. Ectopic expression of miR-638 inhibited OS cell growth in vitro. Subsequently, we identified that PIM1 is the downstream target gene of miR-638 in OS cells, and silencing PIM1 expression phenocopied the inhibitory effect of miR-638 on OS cell proliferation. Furthermore, we observed that PIM1 was overexpressed in OS tissues, and high expression of PIM1 in OS predicted poor overall survival. In summary, we revealed that miR-638 functions as a tumor suppressor through inhibiting PIM1 expression in OS.
Objective: This retrospective study analyzed the factors affecting recurrence in patients after surgery with borderline ovarian tumors and postoperative recurrence and pregnancy after fertility-sparing surgery (FSS), to provide guidance for clinical treatment of borderline ovarian tumors and propose a therapeutic strategy for fertility protection. Methods: A total of 415 patients with borderline ovarian tumors were initially operated on in the gynecology ward of Shengjing Hospital Affiliated with China Medical University from September 1, 2013, to September 1, 2019. Central pathology review and prospective follow-up were carried out. The clinical and pathological data were consulted through the medical record query system of our hospital. The recurrence and pregnancy of the patients were investigated through telephone follow-up and outpatient and inpatient medical records. The influence of clinical and pathological variables on recurrence and pregnancy were evaluated using univariate/multivariate analyses. Results: In this study, 415 patients were collected, of which 21 lost follow-up, and a total of 394 eligible patients were included in the analysis. Among these patients, 25 patients relapsed with a recurrence rate of 6.3% and there were 196 patients with fertility-sparing surgery, of the 63 patients attempting to conceive, 35 were able to attain pregnancy with a pregnancy rate of 55.6%. All patients survived until the follow-up deadline. In univariate and multivariate analyses, FSS, FIGO stage, and micropapillary pattern were independent risk factors for recurrence of BOTs. FIGO stage, micropapillary pattern were independent risk factors for recurrence of BOTs with FSS. The risk of recurrence was not related to omentectomy nor postoperative chemotherapy. While omentectomy and chemotherapy had an impact on the pregnancy rate ( P <0.05) and the pregnancy rate of patients without omentectomy or chemotherapy was higher. Conclusion: Omentectomy did not affect recurrence and it is not recommended as a routine operation. Adjuvant chemotherapy does not reduce the recurrence rate. While omentectomy and chemotherapy had an impact on the pregnancy rate, and both of them should be carried out more carefully in patients with fertility requirements.
Artificial intelligence (AI) is a sort of new technical science which can simulate, extend and expand human intelligence by developing theories, methods and application systems. In the last five years, the application of AI in medical research has become a hot topic in modern science and technology. Gynecological malignant tumors involves a wide range of knowledge, and AI can play an important part in these aspects, such as medical image recognition, auxiliary diagnosis, drug research and development, treatment scheme formulation and other fields. The purpose of this paper is to describe the progress of AI in gynecological malignant tumors and discuss some problems in its application. It is believed that AI improves the efficiency of diagnosis, reduces the burden of clinicians, and improves the effect of treatment and prognosis. AI will play an irreplaceable role in the field of gynecological malignant oncology and will promote the development of medicine and further promote the transformation from traditional medicine to precision medicine and preventive medicine. However, there are also some problems in the application of AI in gynecologic malignant tumors. For example, AI, inseparable from human participation, still needs to be more “humanized”, and needs to further protect patients’ privacy and health, improve legal and insurance protection, and further improve according to local ethnic conditions and national conditions. However, it is believed that with the continuous development of AI, especially ensemble classifier, and deep learning will have a profound influence on the future of medical technology, which is a powerful driving force for future medical innovation and reform.
It is stated that high expression of pyruvate kinase (PKM2) emerges as a significant player in the metabolism and progression of various human malignancies. However, the expression of PKM2 and its association with the prognosis of osteosarcoma had not yet been studied. In the present study, the expression and biological significance of PKM2 in osteosarcoma were investigated. We found that PKM2 expression was elevated in the cancerous tissues and it was more abundant than the adjacent normal tissues (60.2 vs 26.1 %, p < 0.001). Moreover, we showed that high PKM2 expression was positively correlated with Enneking stage (p = 0.006) and distant metastasis (p = 0.007) but not with the age, gender, tumor site, tumor size, histologic grade, alkaline phosphatase (ALP), lactate dehydrogenase (LDH), and local pain of the patients. Furthermore, Kaplan-Meier analysis revealed that the overall survival (OS) for patients with high PKM2 expression was significantly lower than those with low PKM2 expression (p < 0.001). Finally, multivariate analysis revealed that high PKM2 expression was an independent prognostic factor for osteosarcoma patients (p = 0.004). Collectively, these data indicated that elevated PKM2 might serve as a novel target for the treatment of osteosarcoma.
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